Bug Report Issue Triage Assistant

    1

    Transform raw bug reports and logs into structured, evidence-based engineering tickets and triage assessments.

    Free

    3 usesSecurity scanned

    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIDeepSeekDeepSeekMuseMuse+22 more

    Bug Report Issue Triage Assistant

    Example session with this skill installed

    Triage this: User says the 'Save' button on the profile page didn't work. They tried twice on Chrome. No error message shown. Here is the log: [2023-10-01 10:00:05] ERROR: 500 at /api/v1/profile.

    • Read your context and instructions
    • Compiled the bug report issue

    The report has been analyzed. While the user impact is high, the reproduction steps are partially described and require more context for a full fix.

    Executive Triage

    • Issue Title: Profile Save Failure (Internal Server Error 500)
    • One-Line Diagnosis: API endpoint /api/v1/profile returned a 500 error during a profile update attempt.
    • Triage Status: NEEDS MORE INFORMATION
    • Severity: S2 High (Core functionality blocked)
    • Priority: P1 Urgent
    • Confidence: Medium

    Evidence Summary

    • Confirmed Facts: System log shows 500 Internal Server Error at /api/v1/profile.
    • Reported Behavior: 'Save' button non-functional on profile page.
    • Key Evidence: Timestamp 2023-10-01 10:00:05.
    • Missing Information: Request payload, user ID, and full stack trace from the server side.

    Developer-Ready Ticket

    • Title: [BUG] 500 Error on /api/v1/profile Save Action
    • Context: User attempting to update profile settings via web UI.
    • Environment: Chrome (version not provided).
    • Steps to Reproduce:
      1. Navigate to the profile settings page.
      2. Click the 'Save' button.
      3. Observe UI behavior (reported as no error message shown).
    • Expected Result: Profile updates successfully; API returns 200 OK.
    • Actual Result: API returns 500 Internal Server Error.
    • Suspected Component: Backend API (/api/v1/profile).
    • Acceptance Criteria:
      • The /api/v1/profile endpoint returns 200 OK upon valid save requests.
      • UI displays an error state if the API fails, rather than failing silently.

    Issue Quality

    • Score: 45/100
    • Gaps: Missing request/response payloads and specific browser version.

    Next steps

    1. Check server-side logs for the full stack trace corresponding to timestamp 10:00:05.
    2. Request the specific account ID or email from the reporter to check for data-specific edge cases.
    3. Verify if this occurs on other browsers or is isolated to Chrome.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    The Problem

    Developers often receive vague bug reports, incomplete logs, and subjective user complaints. Manually verifying these issues, chasing missing information, and assessing technical severity consumes hours of engineering time better spent on fixes.

    What It Does Analyzes raw bug reports, stack traces, and logs to extract confirmed facts versus reporter hypotheses. Calculates a 0–100 Issue Quality Score based on problem definition, environment context, and available evidence. Determines technical severity (S1–S4) using an evidence-gate system that separates impact from priority. Generates implementation-ready engineering tickets with observable acceptance criteria and reproduction steps. Identifies specific missing information that is currently preventing successful triage. Why This Beats Prompting It Yourself

    Standard prompts often hallucinate missing reproduction steps or invent root causes to be helpful. This skill uses strict evidence-first logic that explicitly labels unknown information as NOT PROVIDED, helping engineers avoid chasing unsupported assumptions or treating a reported issue as independently verified.

    Use Cases Converting messy customer support tickets into structured Jira or GitHub issues. Auditing existing backlogs to identify tickets that lack sufficient evidence for development. Performing rapid security triage on incoming reports to flag potential authentication or data exposure risks. Comparing multiple reports to detect likely duplicates or related regressions. Known Limitations

    This skill does not independently execute code or verify bugs in a live environment. It relies entirely on the text, logs, and artifacts provided in the input.

    Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for Testing & Debugging.

    Does not execute code or access live environments. Relies entirely on provided text, logs, and described artifacts. Cannot verify bugs without supplied evidence.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before buying a skill.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill goes through the trust checks below.

    Security scanned

    Checked by our 8-point scan before listing

    3 uses

    Times used to date

    Free to use

    No account required to browse

    Trust & safety

    Security scan

    Security scan passed 1 month ago

    • Free with an Agensi account

    Permissions

    No special permissions declared or detected

    Listed1 month ago

    What's inside

    Frequently Asked Questions

    The skill requires raw text input such as user descriptions, error logs, or stack traces. It analyzes these to generate structured engineering tickets, severity assessments, and a 'Quality Score' that flags exactly what information is missing.

    This skill is designed for use within any AI agent platform that supports text-based analysis tools and is compatible with major LLM architectures, including GPT-4 and Claude 3.5.

    No, this skill is focused on logical triage and evidence extraction from provided data; it does not access your codebase or execute scripts in a live environment.

    Upon purchase, you receive the full skill configuration, including the evidence-gate logic framework, specific output templates for Jira/GitHub, and setup instructions for your chosen AI agent.

    Unlike standard prompts that may guess missing details, this skill uses 'strict evidence logic' to explicitly label unknowns, preventing developers from wasting time on unverified or 'hallucinated' reproduction steps.

    New in Testing & Debugging

    Free